Evidence map›Paper›PMID 39568644›Full record

ArticlePatterns (New York, N.Y.)2024

Highly accurate and precise determination of mouse mass using computer vision.

Malachy Guzman, Brian Q Geuther, Gautam S Sabnis, Vivek Kumar

Abstract read
In one paragraph

Article in Patterns (New York, N.Y.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Malachy GuzmanThe Jackson Laboratory, Bar Harbor, ME, USA.
Brian Q GeutherThe Jackson Laboratory, Bar Harbor, ME, USA.
Gautam S SabnisThe Jackson Laboratory, Bar Harbor, ME, USA.
Vivek KumarThe Jackson Laboratory, Bar Harbor, ME, USA.

Funding

Establishment and Characterization of Novel Mutant Mouse Models for the Addiction Research CommunityU01DA051235 · NIDA · JACKSON LABORATORY · PI KUMAR, VIVEK · 2021 to 2025
$4.2M
Machine learning based frailty index for the genetically diverse miceR33AG078530 · NIA · JACKSON LABORATORY · PI VIVEK KUMAR · 2024 to 2026
$2.0M
Machine learning based frailty index for the genetically diverse miceR61AG078530 · NIA · JACKSON LABORATORY · PI KUMAR, VIVEK · 2022 to 2023
$946k
Summer Research Experience in Neurobiology at The Jackson LaboratoryR25NS078795 · NINDS · JACKSON LABORATORY · PI Robert W. Burgess, Laura J Muller · 2012 to 2026
$708k
Application of Machine Vision to Determine the Influence of Sleep States and Social Interactions on Vulnerability to Drug AddictionR21DA048634 · NIDA · JACKSON LABORATORY · PI KUMAR, VIVEK · 2019 to 2020
$468k
NIA NIH HHS R33 AG078530NIA NIH HHS R61 AG078530NIDA NIH HHS R21 DA048634NIDA NIH HHS U01 DA051235NINDS NIH HHS R25 NS078795
6 · The paper itself

Abstract

Changes in body mass are key indicators of health in humans and animals and are routinely monitored in animal husbandry and preclinical studies. In rodent studies, the current method of manually weighing the animal on a balance causes at least two issues. First, directly handling the animal induces stress, possibly confounding studies. Second, these data are static, limiting continuous assessment and obscuring rapid changes. A non-invasive, continuous method of monitoring animal mass would have utility in multiple biomedical research areas. We combine computer vision with statistical modeling to demonstrate the feasibility of determining mouse body mass by using video data. Our methods determine mass with a 4.8% error across genetically diverse mouse strains with varied coat colors and masses. This error is low enough to replace manual weighing in most mouse studies. We conclude that visually determining rodent mass enables non-invasive, continuous monitoring, improving preclinical studies and animal welfare.

Indexed as

body massbody weightcomputer visionmachine learningmachine visionmouse diversitysize determinationstatistical modeling

Identifiers

PMID39568644
PMCPMC11573914

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.